CN115592915B - Injection molding machine operation data monitoring and early warning system - Google Patents
Injection molding machine operation data monitoring and early warning system Download PDFInfo
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- 238000001746 injection moulding Methods 0.000 title claims abstract description 99
- 238000012544 monitoring process Methods 0.000 title claims abstract description 58
- 230000000630 rising effect Effects 0.000 claims abstract description 65
- 238000000034 method Methods 0.000 claims abstract description 52
- 230000008569 process Effects 0.000 claims abstract description 39
- 230000002159 abnormal effect Effects 0.000 claims abstract description 28
- 230000007613 environmental effect Effects 0.000 claims abstract description 24
- 230000008859 change Effects 0.000 claims description 38
- 238000010438 heat treatment Methods 0.000 claims description 24
- 238000002347 injection Methods 0.000 claims description 20
- 239000007924 injection Substances 0.000 claims description 20
- 238000004171 remote diagnosis Methods 0.000 claims description 7
- 238000012163 sequencing technique Methods 0.000 claims description 7
- 238000003745 diagnosis Methods 0.000 claims description 6
- 239000012778 molding material Substances 0.000 claims description 5
- 238000013507 mapping Methods 0.000 claims description 4
- 238000004321 preservation Methods 0.000 claims description 4
- 230000005856 abnormality Effects 0.000 claims description 3
- 230000002547 anomalous effect Effects 0.000 claims description 3
- 238000005485 electric heating Methods 0.000 description 9
- 230000009471 action Effects 0.000 description 6
- 238000009413 insulation Methods 0.000 description 3
- 230000007257 malfunction Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 238000010923 batch production Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000001050 lubricating effect Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000000465 moulding Methods 0.000 description 1
- 238000010137 moulding (plastic) Methods 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 238000007711 solidification Methods 0.000 description 1
- 230000008023 solidification Effects 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C45/00—Injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould; Apparatus therefor
- B29C45/17—Component parts, details or accessories; Auxiliary operations
- B29C45/76—Measuring, controlling or regulating
- B29C45/78—Measuring, controlling or regulating of temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76003—Measured parameter
- B29C2945/7604—Temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76451—Measurement means
- B29C2945/76454—Electrical, e.g. thermocouples
- B29C2945/76458—Electrical, e.g. thermocouples piezoelectric
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76494—Controlled parameter
- B29C2945/76531—Temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76929—Controlling method
- B29C2945/76939—Using stored or historical data sets
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
- B29C2945/76—Measuring, controlling or regulating
- B29C2945/76929—Controlling method
- B29C2945/76973—By counting
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Mechanical Engineering (AREA)
- Injection Moulding Of Plastics Or The Like (AREA)
Abstract
The invention relates to the technical field of monitoring of injection molding machines, and particularly discloses an injection molding machine operation data monitoring and early warning system, which comprises: the temperature monitoring module is used for acquiring real-time temperature data of the multi-section position of the charging barrel of the injection molding machine; the environment parameter monitoring module is used for detecting environment parameters of the injection molding machine; the monitoring and early warning module is used for determining a predicted temperature rise curve of the injection molding machine according to the environmental parameters of the injection molding machine, and monitoring and early warning the temperature rise process of the injection molding machine according to real-time temperature data in the temperature rise process of the injection molding machine and comparison of the predicted temperature rise curve of the injection molding machine. The invention can judge whether the temperature rising process of the temperature rising assembly is abnormal or not, further can find the performance attenuation problem of the temperature rising assembly in advance, further avoids the problem of replacing the temperature rising assembly in the injection molding process by replacing in advance, and realizes the accuracy and the advancement of monitoring the performance of the temperature rising assembly.
Description
Technical Field
The invention relates to the technical field of monitoring of injection molding machines, in particular to an operation data monitoring and early warning system of an injection molding machine.
Background
The injection molding machine is a common molding device in the plastic molding process, and generally comprises an injection system, a mold closing system, a hydraulic transmission system, an electric control system, a lubricating system, a heating and cooling system, a safety monitoring system and the like, wherein plastic in a plasticized molten state is injected into a closed mold cavity by virtue of the thrust of a screw or a plunger, and a product is obtained after solidification and shaping.
The injection molding machine needs to be subjected to sectional heating control in the working process, and different positions of the charging barrel reach set temperatures through the temperature controller by arranging a plurality of groups of heating assemblies and thermocouples on the charging barrel.
In the prior art, the heating assembly arranged on the charging barrel is realized by the electric heating ring, the structure is easy to burn out, malfunction and other risks in the long-time use process, and if the electric heating ring malfunctions in the injection molding process, on the one hand, the replacement process affects the injection molding efficiency, on the other hand, the injection molding parameters are required to be readjusted after the maintenance is finished, so that the waste is caused by the injection molding materials in the charging barrel and the hot runner, the malfunction of the electric heating ring is found in advance and the replacement is carried out in advance, and the normal operation of the injection molding machine can be effectively ensured; in the prior art, the method for judging whether the electric heating ring is in failure mainly judges whether the electric heating ring can finish the heating process within a set range, if so, the heating ring is judged to be normal, otherwise, the electric heating ring is judged to be abnormal, the temperature control mode of the existing injection molding machine mainly adopts a PI (proportional integral) control method, when the initial temperature rise of the electric heating ring is slower, the temperature rising efficiency is improved by improving the voltage mode, and obviously, the method for judging the abnormality of the electric heating ring only can perform failure judgment when the electric heating ring completely fails, so the judging process has certain hysteresis.
Disclosure of Invention
The invention aims to provide an injection molding machine operation data monitoring and early warning system, which solves the following technical problems:
how to improve the accuracy and the advance of abnormal monitoring of the temperature rising assembly of the injection molding machine.
The aim of the invention can be achieved by the following technical scheme:
an injection molding machine operational data monitoring and early warning system, the system comprising:
the temperature monitoring module is used for acquiring real-time temperature data of the multi-section position of the charging barrel of the injection molding machine;
the environment parameter monitoring module is used for detecting environment parameters of the injection molding machine;
the monitoring and early warning module is used for determining a predicted temperature rise curve of the injection molding machine according to the environmental parameters of the injection molding machine, and monitoring and early warning the temperature rise process of the injection molding machine according to real-time temperature data in the temperature rise process of the injection molding machine and comparison of the predicted temperature rise curve of the injection molding machine.
In one embodiment, the environmental parameters include ambient temperature and ambient humidity;
measuring standard temperature rise curve models of the injection molding machine in different temperature intervals and humidity intervals in advance;
and determining a predicted temperature rise curve according to the mapping relation between the detected ambient temperature and the ambient humidity and the standard temperature rise curve model.
In one embodiment, the monitoring and early warning process is as follows:
calculating the heating time t required for heating to the set temperature value u When the temperature is raisedInterval t u And predicting the temperature rise time t in the temperature rise curve h And (3) performing comparison:
if t u -t h ≥t p Judging the fault of the temperature rising assembly and carrying out early warning;
if t u -t h ＜t p Then through the formula
Calculating a temperature rise state coefficient P, and combining the temperature rise state coefficient P with a preset threshold value P th And (3) performing comparison:
if P is less than or equal to P th Judging that the temperature rising assembly is in a normal state;
if P > P th Judging that the state of the heating assembly is abnormal and carrying out early warning;
wherein t is p For a preset deviation value T u (t) is a real-time temperature profile over time; t (T) h And (t) is a predicted temperature rise curve.
In one embodiment, the temperature monitoring module is further configured to monitor a temperature value T of the injection molding material at a location on the temperature increasing component l ；
The system also comprises a voltage monitoring module and an operation module;
the voltage monitoring module is used for acquiring a time-varying curve U of the working voltage of the temperature rising assembly;
the operation module is used for counting the single injection quantity;
the monitoring and early warning module is also used for monitoring and early warning according to environmental parameters and T l U, temperature rising component set temperature value T s And analyzing and early warning the heat preservation process of the injection molding machine by the single injection quantity Q.
In one embodiment, the process of analyzing and pre-warning the thermal insulation process of the injection molding machine is as follows:
by Δt=f t (T s -T l Q) calculating the attenuation delta T of the temperature rising component in each injection molding;
wherein f t () A temperature decay function under the current environmental parameters;
according to the environmental parameters, the attenuation delta T and the set temperature value T s Determining a predicted voltage change curve U p According to the voltage real-time change curve U and the predicted voltage change curve U p And comparing, and judging whether the voltage is normal or not according to the comparison result.
In one embodiment, a curve U and a predicted voltage variation curve U p The comparison process comprises the following steps:
by the formula
Calculating a voltage deviation coefficient S, and comparing S with a preset threshold S th And (3) performing comparison:
if S is greater than or equal to S th Judging the fault of the temperature rising assembly and carrying out early warning;
if S is less than S th Judging that the temperature rising assembly is in normal operation;
wherein t is the current time point, t 0 T-t is a preset period of time x ＞t 0 ，t x To start injection time point, U (t) is voltage real-time change curve, U p And (t) is a predicted voltage change curve.
In one embodiment, the system further comprises a fault remote diagnosis module;
the fault remote diagnosis module is used for acquiring key parameter information of the injection molding machine and performing fault diagnosis on the injection molding machine according to the key parameter information;
the key parameter information comprises a current time point parameter and a historical parameter of an injection corresponding product.
In one embodiment, the fault diagnosis process includes:
calculating a parameter average value set according to the historical parameters of the corresponding injection molding product
The current time point parameter { A } 1 、A 2 、…、A N Respectively comparing the two parameters with corresponding parameters in the average value set:
if it is
Judging that the parameter is abnormal;
if it is
Judging that the parameter is compared with the corresponding last injection molding parameter:
if |A i -A il |≥A ith Judging that the parameter is abnormal;
if |A i -A il |＜A ith Judging that the parameter is normal;
wherein N is the total number of parameters, i E [1, N]；A i As the value of the parameter of the i-th item,
for the i-th parameter historical average, A il For the last monitored value of the ith parameter, A ith A preset threshold value for the ith parameter;
and predicting the fault type according to the type of the abnormal parameter item.
In one embodiment, the method for predicting the fault type is as follows:
setting key parameter items aiming at each fault type, and sequencing the key parameter items according to the association degree;
by the formula
Calculating a probability value X of each fault type;
wherein θ j A weight coefficient of the j-th key parameter item, theta j+1 ＞θ j ；π j Is the anomaly coefficient of the j-th key parameter item, pi when the key parameter item is anomalous j =1, otherwise, pi j ＝0；
And acquiring probability values X of all fault types, sequencing, and selecting the first fault type sequenced by the probability values X as the predicted fault type.
The invention has the beneficial effects that:
(1) According to the invention, the temperature rising curve of the temperature rising assembly in the production state is determined according to the environmental parameter information of the injection molding machine, the implementation temperature change curve is formed according to the detected real-time temperature data, and whether the temperature rising process of the temperature rising assembly is abnormal or not can be judged through comparison of the change curves, so that the performance attenuation problem of the temperature rising assembly can be found in advance, the problem of replacing the temperature rising assembly in the injection molding process is avoided through an early replacement mode, and the accuracy and the advancement of monitoring the performance of the temperature rising assembly are realized.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of an injection molding machine operation data monitoring and early warning system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, in one embodiment, an injection molding machine operation data monitoring and early warning system is provided, the system comprising:
the temperature monitoring module is used for acquiring real-time temperature data of the multi-section position of the charging barrel of the injection molding machine;
the environment parameter monitoring module is used for detecting environment parameters of the injection molding machine;
the monitoring and early warning module is used for determining a predicted temperature rise curve of the injection molding machine according to the environmental parameters of the injection molding machine, and monitoring and early warning the temperature rise process of the injection molding machine according to real-time temperature data in the temperature rise process of the injection molding machine and comparison of the predicted temperature rise curve of the injection molding machine.
Through the technical scheme, the temperature rising curve of the temperature rising assembly in the production state is determined according to the environmental parameter information of the injection molding machine, meanwhile, the temperature change curve is formed according to the detected real-time temperature data, whether the temperature rising assembly reaches the set temperature in the set time can be judged through comparison of the change curves, whether the temperature rising process of the temperature rising assembly is abnormal can be judged, the problem of performance attenuation of the temperature rising assembly can be found in advance, the problem of replacement of the temperature rising assembly in the injection molding process is avoided in advance, and accuracy and advancement of monitoring of the performance of the temperature rising assembly are realized.
As one embodiment of the present invention, the environmental parameters include an ambient temperature and an ambient humidity;
taking a temperature rising component at one position point of a charging barrel as an example, measuring a standard temperature rising curve model of the injection molding machine in different temperature intervals and humidity intervals in advance;
and determining a predicted temperature rise curve according to the mapping relation between the detected ambient temperature and the ambient humidity and the standard temperature rise curve model.
According to the technical scheme, the environment parameters influence the actual temperature rising process of the temperature rising assembly, so that the environment temperature and the environment humidity are obtained through the environment parameter monitoring module, the predicted temperature rising curve is determined according to the mapping relation of the standard temperature rising curve model, the reference standard can be determined, and the accurate reference standard is provided for judging the temperature rising process of the temperature rising assembly.
It should be noted that, the standard temperature rise curve model of the injection molding machine is obtained by pre-measurement, a plurality of sections are set according to the temperature range of the environment where the injection molding machine is located, a plurality of sections are set according to the humidity range of the environment where the injection molding machine is located, the temperature rise curves of the same type of temperature rise components are measured respectively in different temperature sections and different humidity sections, and then the standard temperature rise curve model is formed, so that the corresponding predicted temperature rise curve can be obtained through the detected environmental temperature and environmental humidity.
As one implementation mode of the invention, the process of monitoring and early warning is as follows:
calculating the heating time t required for heating to the set temperature value u When the temperature is raisedInterval t u And predicting the temperature rise time t in the temperature rise curve h And (3) performing comparison:
if t u -t h ≥t p Judging the fault of the temperature rising assembly and carrying out early warning;
if t u -t h ＜t p Then through the formula
Calculating a temperature rise state coefficient P, and combining the temperature rise state coefficient P with a preset threshold value P th And (3) performing comparison:
if P is less than or equal to P th Judging that the temperature rising assembly is in a normal state;
if P > P th Judging that the state of the heating assembly is abnormal and carrying out early warning;
wherein t is p For a preset deviation value T u (t) is a real-time temperature profile over time; t (T) h And (t) is a predicted temperature rise curve.
Through the above technical solution, the present embodiment provides a method for monitoring and early warning, specifically, firstly, performing preliminary comparison according to the heating time, and heating the time t u And predicting the temperature rise time t in the temperature rise curve h Comparing, when t u -t h ≥t p In this case, since the temperature rise time is long, it is determined that the temperature rise module is defective, when t u -t h ＜t p At the time, the actual temperature rise time t u And forecast heating time t h The difference is small, so further analysis; it should be noted that t does not occur due to the limitation of the voltage u Far less than t h Is a condition of (2).
In the further analysis, the formula is passed
Calculating a temperature rise state coefficient P, wherein the temperature rise state coefficient P represents the difference value of the area surrounded by a real-time temperature change curve and a predicted temperature rise curve according to a formula, and the temperature rise state coefficient P is obtained by combining P with a preset threshold P th When P is less than or equal to P, the comparison is carried out th At the same time, the real-time temperature changes with timeThe difference between the values of the melting curve and the predicted heating curve is smaller, and the two curves are higher in fit, so that the heating assembly is judged to be normal, and when P is more than P th The method has the advantages that the fact that the real-time temperature change curve and the predicted temperature rise curve have larger deviation is explained, so that the problem of performance of the temperature rise assembly is judged, early warning is conducted, and management staff is reminded of timely replacing the temperature rise assembly.
It should be noted that t in the above technical scheme p 、P th The data measured by the plurality of groups of temperature rising components with the same model are selected by fitting, and compared with the data, whether the temperature rising components are abnormal or not can be judged.
As one embodiment of the invention, the temperature monitoring module is also used for monitoring the temperature value T of the injection molding material at one position on the temperature rising assembly l ；
The system also comprises a voltage monitoring module and an operation module;
the voltage monitoring module is used for acquiring a time-varying curve U of the working voltage of the heating assembly;
the operation module is used for counting the single injection quantity;
the monitoring and early warning module is also used for monitoring and early warning according to environmental parameters and T l U, temperature rising component set temperature value T s And analyzing and early warning the heat preservation process of the injection molding machine by the single injection quantity Q.
Through the above technical scheme, the present embodiment provides a method for monitoring and analyzing a temperature rising assembly in a batch production process of an injection molding machine, specifically, a temperature monitoring module is used to obtain a temperature T before an injection molding material enters the temperature rising assembly l And then detecting a working voltage change curve U of the temperature rising assembly along with time according to the voltage monitoring module, and counting single injection quantity through the operation module, so that the action voltage can be predicted according to environmental parameters, action injection quantity and temperature change quantity, and whether the temperature rising assembly has an abnormal problem or not can be judged by comparing the actual voltage U with the predicted action voltage.
As one implementation mode of the invention, the process of analyzing and early warning in the thermal insulation process of the injection molding machine is as follows:
by Δt=f t (T s -T l Q) calculating the attenuation delta T of the temperature rising component in each injection molding;
wherein f t () A temperature decay function under the current environmental parameters;
according to the environmental parameters, the attenuation delta T and the set temperature value T s Determining a predicted voltage change curve U p According to the voltage real-time change curve U and the predicted voltage change curve U p And comparing, and judging whether the voltage is normal or not according to the comparison result.
Through the above technical scheme, this embodiment provides a method for analyzing and early warning in the thermal insulation process of an injection molding machine, firstly according to Δt=f t (T s -T l Q) calculate the attenuation DeltaT of the temperature rising component in each injection, wherein f t () Determining a temperature attenuation coefficient delta T according to a single injection amount and a temperature variation amount as a temperature attenuation function under the current environmental parameters, wherein the temperature variation amount is according to the heated temperature T s And temperature T before heating l Determine, therefore, by Δt=f t (T s -T l Q), the attenuation amount of the temperature of each injection molding operation can be determined, and the temperature value T is set by the attenuation amount s Determining a predicted voltage change curve U p Then, the voltage real-time change curve U and the predicted voltage change curve U are passed p And then can judge whether the voltage of the voltage heating assembly is abnormal or not, thereby realizing the early warning of the heating assembly.
Further, the temperature decay function in the present embodiment is obtained by measuring in advance under different environmental parameters, and is compared with the single injection quantity Q and the temperature variation quantity (T s -T l ) Positive correlation, i.e. when the single shot is large, there is more loss of temperature, when the temperature regulation is large, i.e. (T) s -T l ) When larger, the loss to temperature is also larger.
Further to the predicted voltage change curve U p The method of determination is described by first, according to the environmental parameters and the set temperature value T s The voltage change curve under the state of non-injection molding loss can be obtained by pre-preparing the standard temperature rising componentThe voltage change curve under the non-injection loss state is adjusted by the calculated attenuation delta T, and the voltage change curve U can be obtained and predicted p The process comprises determining the increment voltage delta U according to the attenuation delta T, combining the increment voltage delta U with the voltage change curve under the non-injection loss state, and obtaining the predicted voltage change curve U p The method comprises the steps of carrying out a first treatment on the surface of the It should be noted that, the time point when the voltage increasing amount Δu increases is determined according to the time point of each injection molding, and the specific combination is easily implemented by the prior art, which is not described in detail herein.
As one embodiment of the present invention, the voltage real-time variation curve U and the predicted voltage variation curve U p The comparison process comprises the following steps:
by the formula
Calculating a voltage deviation coefficient S, and comparing S with a preset threshold S th And (3) performing comparison:
if S is greater than or equal to S th Judging the fault of the temperature rising assembly and carrying out early warning;
if S is less than S th Judging that the temperature rising assembly is in normal operation;
wherein t is the current time point, t 0 T-t is a preset period of time x ＞t 0 ，t x To start injection time point, U (t) is voltage real-time change curve, U p And (t) is a predicted voltage change curve.
Through the above technical scheme, the present embodiment provides a voltage real-time change curve U and a predicted voltage change curve U p The comparison method is realized through the formula
Calculating a voltage deviation coefficient S, and comparing S with a preset threshold S th Comparing, it is obvious that when S is greater than or equal to S th When the temperature-raising assembly is in a high temperature state, the superposition of the actual action voltage curve and the preset voltage curve is poor, and the fact that the actual action voltage is large can meet the heat-preserving requirement is indicated, so that the failure probability of the temperature-raising assembly is large, and thenJudging the fault of the temperature rising component and carrying out early warning, when S is less than S th When the temperature rising assembly is in the normal operation state, the actual action voltage is close to the preset voltage, so that the temperature rising assembly is judged to be in the normal operation state; thus, the real-time voltage change curve U and the predicted voltage change curve U are used for p The temperature rising assembly can be judged in advance through abnormality of the temperature rising assembly, and then management staff is warned to replace the temperature rising assembly with performance in time through early warning.
As one embodiment of the present invention, the system further comprises a fault remote diagnosis module;
the fault remote diagnosis module is used for acquiring key parameter information of the injection molding machine and carrying out fault diagnosis on the injection molding machine according to the key parameter information;
the key parameter information comprises the current time point parameter and the historical parameter of the injection corresponding product.
Through the technical scheme, by setting the fault remote diagnosis module, the fault type can be analyzed when the related key parameters of the injection molding machine are abnormal, and then the repair personnel can be assisted in rapidly finding out the fault point, specifically, the current time point parameters and the historical parameters of the injection molding corresponding products are obtained, and the accurate judgment of the fault can be realized through the deviation of the parameters.
As one embodiment of the present invention, the fault diagnosis process includes:
calculating a parameter average value set according to the historical parameters of the corresponding injection molding product
The current time point parameter { A } 1 、A 2 、…、A N Respectively comparing the two parameters with corresponding parameters in the average value set:
if it is
Judging that the parameter is abnormal;
if it is
Judging that the parameter is compared with the corresponding last injection molding parameter:
if |A i -A il |≥A ith Judging that the parameter is abnormal;
if |A i -A il |＜A ith Judging that the parameter is normal;
wherein N is the total number of parameters, i E [1, N]；A i As the value of the parameter of the i-th item,
for the i-th parameter historical average, A il For the last monitored value of the ith parameter, A ith A preset threshold value for the ith parameter;
and predicting the fault type according to the type of the abnormal parameter item.
Through the technical scheme, the embodiment calculates the parameter average value set according to the historical injection molding parameters of the current injection molding product
Comparing the real-time detection parameters with the corresponding parameters of the average value set to further judge whether the parameters have larger deviation, specifically, firstly judging whether +.>
Obviously, when the parameter is yes, the fact that the actual detection parameter and the average value corresponding to the parameter generate larger deviation is indicated, so that the parameter is judged to be abnormal; when (when)
When the parameter is larger than the previous parameter, judging whether the parameter is changed greatly, when the parameter is |A i -A il |≥A ith When the parameter is compared with the previous parameter, the parameter is determined to be abnormal by indicating that the parameter is greatly changedIs a parameter term of (a).
When it is required to be described, for the same injection molding product, the parameters of the injection molding process have certain deviation, but the difference is in a reasonable range, and meanwhile, for the injection molding process with continuous time, the variation of the related parameters is smaller.
As one embodiment of the present invention, the method for predicting the fault type is:
setting key parameter items aiming at each fault type, and sequencing the key parameter items according to the association degree;
by the formula
Calculating a probability value X of each fault type;
wherein θ j A weight coefficient of the j-th key parameter item, theta j+1 ＞θ j ；π j Is the anomaly coefficient of the j-th key parameter item, pi when the key parameter item is anomalous j =1, otherwise, pi j ＝0；
And acquiring probability values X of all fault types, sequencing, and selecting the first fault type sequenced by the probability values X as the predicted fault type.
Through the technical scheme, the relevance of the key parameter items and the fault types is determined according to the common problems of the injection molding machine and the occurrence probability of the abnormal items of the key parameters when each problem occurs, then the key parameter items are ordered according to the relevance aiming at each fault type, and then the relevance is determined according to the formula
Calculating probability value X of each fault type, and when the key parameter item is abnormal, making pi j When the key parameter item is normal, let pi be =1 j Because the probability value X of each fault type can be determined according to the abnormal key parameter item by accumulating the products of the weight coefficient and the abnormal coefficient, and then the fault type closest to the actual condition can be accurately predicted by sequencing the probability value X and selecting the first sequenced fault type as the predicted fault type.
The weight coefficient θ j Judging according to the abnormal probability of the j-th key parameter item of the fault type in the historical data, and when the probability is larger, theta j The numerical value is also larger.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (3)
1. An injection molding machine operation data monitoring and early warning system, the system comprising:
the temperature monitoring module is used for acquiring real-time temperature data of the multi-section position of the charging barrel of the injection molding machine;
the environment parameter monitoring module is used for detecting environment parameters of the injection molding machine;
the monitoring and early warning module is used for determining a predicted temperature rise curve of the injection molding machine according to the environmental parameters of the injection molding machine, and monitoring and early warning the temperature rise process of the injection molding machine according to the comparison of real-time temperature data in the temperature rise process of the injection molding machine and the predicted temperature rise curve of the injection molding machine;
the environmental parameters include an ambient temperature and an ambient humidity;
measuring standard temperature rise curve models of the injection molding machine in different temperature intervals and humidity intervals in advance;
determining a predicted temperature rise curve according to the mapping relation between the detected ambient temperature and the ambient humidity and the standard temperature rise curve model;
the monitoring and early warning process comprises the following steps:
calculating the heating time t required for heating to the set temperature value u Will raise the temperature for a period t u And predicting the temperature rise time t in the temperature rise curve h And (3) performing comparison:
if t u -T h ≥t p Judging the fault of the temperature rising assembly and carrying out early warning;
if t u -T h ＜t p Then through the formula
Calculating a temperature rise state coefficient P, and combining the temperature rise state coefficient P with a preset threshold value P th And (3) performing comparison:
if P is less than or equal to P th Judging that the temperature rising assembly is in a normal state;
if P > P th Judging that the state of the heating assembly is abnormal and carrying out early warning;
wherein t is p For a preset deviation value T u (t) is a real-time temperature profile over time; t (T) h And (t) is a predicted temperature rise curve.
2. The injection molding machine operation data monitoring and early warning system according to claim 1, wherein the temperature monitoring module is further configured to monitor a temperature value T of the injection molding material at a position on the temperature raising assembly l ；
The system also comprises a voltage monitoring module and an operation module;
the voltage monitoring module is used for acquiring a time-varying curve U of the working voltage of the temperature rising assembly;
the operation module is used for counting the single injection quantity;
the monitoring and early warning module is also used for monitoring and early warning according to environmental parameters and T l U, temperature rising component set temperature value T s Analyzing and early warning the heat preservation process of the injection molding machine by the single injection quantity Q;
the process of analyzing and early warning in the heat preservation process of the injection molding machine is as follows:
by Δt=f t (T s -T l Q) calculating the attenuation delta T of the temperature rising component in each injection molding;
wherein f t () A temperature decay function under the current environmental parameters;
according to the environmental parameters, the attenuation delta T and the set temperature value T s Determining a predicted voltage change curve U p According to the voltage real-time change curve U and the predicted voltage change curve U p Comparing, and judging whether the voltage is normal or not according to the comparison result;
electric compacting machineTime change curve U and predicted voltage change curve U p The comparison process comprises the following steps:
by the formula
Calculating a voltage deviation coefficient S, and comparing S with a preset threshold S th And (3) performing comparison:
if S is greater than or equal to S th Judging the fault of the temperature rising assembly and carrying out early warning;
if S is less than S th Judging that the temperature rising assembly is in normal operation;
wherein t is the current time point, t 0 T-t is a preset period of time x ＞t 0 ，t x To start injection time point, U (t) is voltage real-time change curve, U p And (t) is a predicted voltage change curve.
3. The injection molding machine operation data monitoring and early warning system according to claim 1, further comprising a fault remote diagnosis module;
the fault remote diagnosis module is used for acquiring key parameter information of the injection molding machine and performing fault diagnosis on the injection molding machine according to the key parameter information;
the key parameter information comprises current time point parameters and historical parameters of injection corresponding products;
the fault diagnosis process comprises the following steps:
calculating a parameter average value set according to the historical parameters of the corresponding injection molding product
The current time point parameter { A } 1 、A 2 、…、A N Respectively comparing the two parameters with corresponding parameters in the average value set:
if it is
Judging that the parameter is abnormal;
if it is
Judging that the parameter is compared with the corresponding last injection molding parameter:
if |A i -A il |≥A ith Judging that the parameter is abnormal;
if |A i -A il |＜A ith Judging that the parameter is normal;
wherein N is the total number of parameters, i E [1, N]；A i As the value of the parameter of the i-th item,
for the i-th parameter historical average, A il For the last monitored value of the ith parameter, A ith A preset threshold value for the ith parameter;
predicting fault types according to the types of the abnormal parameter items;
the fault type prediction method comprises the following steps:
setting key parameter items aiming at each fault type, and sequencing the key parameter items according to the association degree;
by the formula
Calculating a probability value X of each fault type;
wherein θ j A weight coefficient of the j-th key parameter item, theta j+1 ＞θ j And θ is as follows j Judging the probability of the j-th key parameter item abnormality according to the fault type in the historical data; m is the key parameter item number; pi j Is the anomaly coefficient of the j-th key parameter item, pi when the key parameter item is anomalous j =1, otherwise, pi j ＝0；
And acquiring probability values X of all fault types, sequencing, and selecting the first fault type sequenced by the probability values X as the predicted fault type.
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| CN116300690B (en) * | 2023-05-17 | 2023-07-25 | 济宁联威车轮制造有限公司 | Radial drilling machine fault monitoring and early warning system based on edge calculation |
| CN117312879A (en) * | 2023-11-09 | 2023-12-29 | 江门塚田正川科技有限公司 | Injection molding machine production data supervision and early warning method, system and medium |
| CN117283743B (en) * | 2023-11-23 | 2024-02-02 | 绵阳华远同创科技有限公司 | Resin production molding processing flow prediction control system and method |
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